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1. 发明申请

US20190224480A1 SYSTEM AND METHOD TO CUE SPECIFIC MEMORY RECALLS WHILE AWAKE 审中-公开
公开(公告)号：US20190224480A1
公开(公告)日：2019-07-25
申请号：US16374433
申请日：2019-04-03
申请人： HRL Laboratories, LLC
发明人： Michael D. Howard , Praveen K. Pilly , Michael J. Daily
IPC分类号： A61N1/36 , A61N1/04
摘要： Described is a system for cueing a specific memory in a waking state. The system sends an initiation signal to a memory recall controller to select a stored stimulation pattern previously associated with a specific memory of an event. The system signals to a memory recall controller to initiate delivery of the selected stimulation pattern to a brain in a waking state for a duration of the event via a brain stimulation system. Following completion of the event, the system signals for the memory recall controller to stop the brain stimulation system from delivering the selected stimulation pattern.

2. 发明授权

US09880553B1 System and method for robot supervisory control with an augmented reality user interface 有权
公开(公告)号：US09880553B1
公开(公告)日：2018-01-30
申请号：US15139039
申请日：2016-04-26
申请人： HRL Laboratories, LLC
发明人： Heiko Hoffmann , Michael J. Daily
IPC分类号： G05D1/00 , B25J9/16 , B25J19/02 , G05D1/02 , H04N13/02 , H04N5/225 , G06T11/60 , G06F3/0484
CPC分类号： G05D1/0038 , B25J9/1689 , B25J19/023 , G05D1/0016 , G05D1/0251 , G05D2201/0217 , G06F3/04842 , G06F3/04845 , G06T11/60 , H04N5/2253 , H04N13/204 , Y10S901/01
摘要： Described is a system for robot supervisory control. The system includes an operator device that receives camera imagery from a camera mounted on a robot and three-dimensional (3D) data from a 3D sensor mounted on the robot. The user interface displays a two-dimensional (2D) view of the scene from the camera and 3D sensor data. One or more object markers of objects in the scene are overlaid on the 2D view or 3D sensor data. Viewing the scene, the user can choose a robotic action from a library of actions, which generates a simulation of the robot performing the selected action. The simulation is then rendered and overlaid on top of the 3D sensor data. Moreover, the simulation shows the expected variability of the robot's action. Based on the simulation's outcome, the user can approve and trigger the execution of the action in the real robot.

3. 发明授权

US11278722B2 System and method to cue specific memory recalls while awake 有权
公开(公告)号：US11278722B2
公开(公告)日：2022-03-22
申请号：US16374433
申请日：2019-04-03
申请人： HRL Laboratories, LLC
发明人： Michael D. Howard , Praveen K. Pilly , Michael J. Daily
IPC分类号： A61N1/36 , A61N1/04
摘要： Described is a system for cueing a specific memory in a waking state. The system sends an initiation signal to a memory recall controller to select a stored stimulation pattern previously associated with a specific memory of an event. The system signals to a memory recall controller to initiate delivery of the selected stimulation pattern to a brain in a waking state for a duration of the event via a brain stimulation system. Following completion of the event, the system signals for the memory recall controller to stop the brain stimulation system from delivering the selected stimulation pattern.

4. 发明授权

US09378420B1 System for detecting an object of interest in a scene 有权
标题翻译：用于检测场景中的感兴趣对象的系统
公开(公告)号：US09378420B1
公开(公告)日：2016-06-28
申请号：US14292416
申请日：2014-05-30
申请人： HRL Laboratories, LLC
发明人： Terrell N. Mundhenk , A. Arturo Flores , Shinko Y Cheng , Howard Neely, III , Michael J. Daily
IPC分类号： G06K9/00
CPC分类号： G06K9/00624 , G06K9/00228 , G06K9/4642 , G06K9/4671 , G06K9/4676 , G06K9/6269
摘要： The present invention relates to a system for detecting an object of interest in a scene. The system operates by receiving an image frame of a scene and extracting features from the image frame, the features being descriptors. The descriptors are quantized to generate PHOW features. A sliding window protocol is implemented to slide a window over the image and analyze the PHOW features that fall inside the window. Finally, the system determines if the PHOW features represent the object of interest and, if so, then designates the window as a location in the image with a detected object of interest.
摘要翻译：本发明涉及一种用于检测场景中的感兴趣对象的系统。该系统通过接收场景的图像帧并从图像帧中提取特征来操作，特征是描述符。描述符被量化以产生PHOW特征。实现滑动窗口协议以将窗口滑过图像并分析落入窗口内的PHOW特征。最后，系统确定PHOW特征是否表示感兴趣的对象，如果是，则将窗口指定为图像中具有感兴趣对象的位置。

5. 发明授权

US09336239B1 System and method for deep packet inspection and intrusion detection 有权
标题翻译：深度包检测和入侵检测的系统和方法
公开(公告)号：US09336239B1
公开(公告)日：2016-05-10
申请号：US13742675
申请日：2013-01-16
申请人： HRL Laboratories, LLC
发明人： Heiko Hoffmann , Michael J. Daily , Gavin D. Holland , Karim El Defrawy
IPC分类号： G06F17/30 , G06N3/08 , G06K9/62
CPC分类号： G06F17/30247 , G06K9/62 , G06N3/049 , G06N3/08 , H04L63/1416
摘要： The present invention relates to a system for deep packet inspection and intrusion detection. The system uses a pattern matching module receiving as an input a data stream in a neural network. Neurons are activated such that when active, the neuron fires to all connecting output neurons to form a neuron spike, each neuron spike from the assigned neuron to a connecting output neuron having a delay. A delay is associated with each input character in the pattern, such that a position of each input character relative to an end of the pattern is stored in an alphabet-pattern-delay matrix (APDFM). An activation matrix (AM) is used to match each input character with a stored pattern to generate a similarity match and determine if the string of characters is the stored pattern.
摘要翻译：本发明涉及一种深度包检测和入侵检测系统。该系统使用模式匹配模块，在神经网络中接收数据流作为输入。神经元被激活，使得当活动时，神经元激发到所有连接的输出神经元以形成神经元尖峰，每个神经元从分配的神经元尖峰到具有延迟的连接输出神经元。延迟与图案中的每个输入字符相关联，使得每个输入字符相对于图案的末尾的位置被存储在字母图案延迟矩阵（APDFM）中。激活矩阵（AM）用于将每个输入字符与存储的模式相匹配以生成相似性匹配，并确定字符串是否是存储的模式。

6. 发明授权

US08788030B1 Systems, methods, and apparatus for neuro-robotic tracking point selection 有权
标题翻译：用于神经机器人跟踪点选择的系统，方法和装置
公开(公告)号：US08788030B1
公开(公告)日：2014-07-22
申请号：US13910828
申请日：2013-06-05
申请人： HRL Laboratories, LLC
发明人： David W. Payton , Michael J. Daily
IPC分类号： A61B5/04
CPC分类号： A61B34/30 , A61B5/0476 , G06F3/015
摘要： Systems, methods, and apparatus for neuro-robotic tracking point selection are disclosed. A described example robot control system includes a feature and image presenter, a classifier, a visual-servo controller, and a robot interface. The feature and image presenter is to display an image of an object, emphasize one of more potential trackable features of the object, receive a selection of the emphasized feature, and determine an offset from the selected feature as a goal. The classifier is to classify a mental response to the emphasized features, and to determine that the mental response corresponds to the selection of one of the emphasized features. The visual-servo controller is to track the emphasized feature corresponding to an identified brain signal. The robot interface is to generate control information to effect a robot action based on the emphasized feature, the visual-servo controller to track the emphasized feature while the robot action is being effected.
摘要翻译：公开了用于神经机器人跟踪点选择的系统，方法和装置。所描述的示例性机器人控制系统包括特征和图像呈现器，分类器，视觉伺服控制器和机器人接口。特征和图像呈现者是显示对象的图像，强调对象的更多潜在的可跟踪特征之一，接收强调特征的选择，以及确定所选特征的偏移为目标。分类器是对强调特征进行心理反应分类，并确定心理反应对应于强调特征之一的选择。视觉伺服控制器是跟踪与识别的脑信号相对应的强调特征。机器人界面是基于强调特征产生控制信息来实现机器人动作，视觉伺服控制器在机器人动作进行时跟踪强调特征。

7. 发明授权

US10002430B1 Training system for infield training of a vision-based object detector 有权
公开(公告)号：US10002430B1
公开(公告)日：2018-06-19
申请号：US15141416
申请日：2016-04-28
申请人： HRL Laboratories, LLC
发明人： Terrell N. Mundhenk , A. Arturo Flores , Howard Neely, III , Michael J. Daily
IPC分类号： G06T7/00 , G06N99/00
CPC分类号： G06N20/00 , G06K9/00771 , G06K9/4671 , G06K9/6265 , G06K9/6287 , G06T7/73 , G06T2207/20081
摘要： Described is a training system for training a vision-based object detector. The system is configured to run an object detector on an image of a cleared scene to detect objects in the cleared scene. The object detector includes a support vector machine (SVM) or similar classifier with a feature model to generate an SVM score for object features and a spatial bias threshold to generate augmented object scores. The system designated detected objects in the cleared scene as false detections and, based on that, updates at least one of the feature model and spatial bias threshold to designate the false detections as background. The updated feature model or updated spatial bias threshold are then stored for use in object detection.

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